Title
Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.
Abstract
In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98.30% (+/- 1.26%) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.
Year
DOI
Venue
2016
10.3390/s16081221
SENSORS
Keywords
Field
DocType
Myo armband,eLearning,gesture recognition,surface EMG,smart wearable sensors,hand hygiene,hospital-acquired infections,nosocomial infections
Units of measurement,Wearable computer,Gesture,Simulation,Gesture recognition,Electronic engineering,Human–computer interaction,Wearable Electronic Device,Hygiene,Engineering,Artificial neural network,Hidden Markov model
Journal
Volume
Issue
Citations 
16
8.0
2
PageRank 
References 
Authors
0.35
4
5
Name
Order
Citations
PageRank
Ekaterina Kutafina173.63
David Laukamp221.03
Ralf Bettermann320.35
Ulrik Schroeder429178.85
Stephan Jonas5358.92